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Episodic memory in aspects of brain information transfer by resting-state network topology.
Yan, Tianyi; Wang, Gongshu; Wang, Li; Liu, Tiantian; Li, Ting; Wang, Luyao; Chen, Duanduan; Funahashi, Shintaro; Wu, Jinglong; Wang, Bin; Suo, Dingjie.
Afiliação
  • Yan T; School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
  • Wang G; School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
  • Wang L; School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
  • Liu T; School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
  • Li T; School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
  • Wang L; School of Mechatronical Engineering, Intelligent Robotics Institute, Beijing Institute of Technology, Beijing 100081, China.
  • Chen D; School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
  • Funahashi S; Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing 100081, China.
  • Wu J; School of Mechatronical Engineering, Intelligent Robotics Institute, Beijing Institute of Technology, Beijing 100081, China.
  • Wang B; Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing 100081, China.
  • Suo D; International Joint Research Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing 100081, China.
Cereb Cortex ; 32(22): 4969-4985, 2022 11 09.
Article em En | MEDLINE | ID: mdl-35174851
Cognitive functionality emerges due to neural interactions. The interregional signal interactions underlying episodic memory are a complex process. Thus, we need to quantify this process more accurately to understand how brain regions receive information from other regions. Studies suggest that resting-state functional connectivity (FC) conveys cognitive information; additionally, activity flow estimates the contribution of the source region to the activation pattern of the target region, thus decoding the cognitive information transfer. Therefore, we performed a combined analysis of task-evoked activation and resting-state FC voxel-wise by activity flow mapping to estimate the information transfer pattern of episodic memory. We found that the cinguloopercular (CON), frontoparietal (FPN) and default mode networks (DMNs) were the most recruited structures in information transfer. The patterns and functions of information transfer differed between encoding and retrieval. Furthermore, we found that information transfer was a better predictor of memory ability than previous methods. Additional analysis indicated that structural connectivity (SC) had a transportive role in information transfer. Finally, we present the information transfer mechanism of episodic memory from multiple neural perspectives. These findings suggest that information transfer is a better biological indicator that accurately describes signal communication in the brain and strongly influences the function of episodic memory.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Memória Episódica Tipo de estudo: Prognostic_studies Idioma: En Revista: Cereb Cortex Assunto da revista: CEREBRO Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Memória Episódica Tipo de estudo: Prognostic_studies Idioma: En Revista: Cereb Cortex Assunto da revista: CEREBRO Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China